The National Institutes of Health (NIH) intramural research program is the largest, single performer of life science research in the world. Among the most contentious policy issues in Washington today are threats to the integrity of the life science enterprise arising from relationships between NIH scientists and administrators and private industry. Issues of bias in science, secrecy and conflicts of interest swirl around discussions of these government industry relationships (GIRs). In January of 2006, the Director of the NIH implemented "new ethics rules" that ban consulting and restrict other forms of relationships between NIH intramural scientists' and industry. However, unlike relationships between academic scientists and industry, at present there are no systemic data regarding the nature, extent and consequences of GIRs. The specific aims of this study are: 1. To document the prevalence of various types of GIRs among intramural scientists [and administrators and the factors that predicted those relationships; 2. To document the potential benefits of GIRs among intramural scientists and administrators in the NIH and the factors that predict those benefits; 3. To document the potential risks of GIRs for research integrity among intramural scientists and administrators in the NIH, and the factors that predict those risks; 4. To document the impact, if any, of the new ethics rules on relationships between NIH intramural scientists and administrators and industry. The proposed methodology has been used extensively by our research team. The study will involve 3 qualitative focus groups and 10 personal interviews and a quantitative survey of 1000 NIH intramural scientists and administrators. As the primary data collection method, the mailed survey will collect data on the frequency of subjects' relationships with industry, the benefits and risks of those relationships and the impact, if any of the new ethics rules that went into effect in January of 2006. The data from the focus groups and interviews will be analyzed using standard qualitative techniques. The quantitative data from the survey will be analyzed using standard analytical techniques such as general linear regression and logistic regression. When completed, the results will be published in at least two papers in high profile journals and presented at national conferences. The results of this study could inform the disclosure and management of government industry relationships, provide benchmark data for major policy initiatives in the government sector and provide a fuller understanding of the complex nature of the modern life science enterprise. [unreadable] [unreadable] [unreadable]